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objective will be to develop algorithms for predicting and planning the evolution of local energy systems (microgrids) over a time horizon of several years, using machine learning and numerical optimization
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: - Apply unsupervised machine learning concepts to the analysis of continuous seismograms recorded in the vicinity of active volcanoes, in order to extract information about the state of the volcano and the
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mechanical activity at the same time. In this context, the use of mathematical models and machine learning methods can be relevant to integrate physiological knowledge in data analysis and to analyze
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available1Company/InstituteInriaCountryFranceGeofield Where to apply Website https://illbeback.ai/job/phd-position-f-m-machine-learning-for-efficient-bimoda… STATUS: EXPIRED
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Research Framework Programme? HE / MSCA Marie Curie Grant Agreement Number 101120240 Is the Job related to staff position within a Research Infrastructure? No Offer Description Machine Learning for Quantum
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statistics Excellent background in statistical/machine learning Experience in computer vision is a plus Strong motivation for medical and societal applications of computational methods Knowledge of biology and
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experimental campaigns to acquire the data required for his thesis, as well as for the MONI-TREE project as a whole. The PhD will take place in LETG-Rennes, with expected missions to ONERA's Palaiseau for works
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PhD offer in Channel charting and machine learning techniques for massive cell-free MIMO 6G networks
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Title Channel charting and machine learning techniques for minimizing the power consumption of massive
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controlling these molecular networks in vivo . This will be achieved using scRNAseq, spatial transcriptomics, advanced machine learning approaches, and genetic approaches to manipulate the expression of
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specialized in Technology-Enhanced Learning (TEL) and Human-Computer Interaction (HCI). In particular, SICAL has extensive experience in behavior analysis using multimodal data in different contexts, including